The noncontact biometric identification device authenticates a user using his or her biometric features, such as the fingerprints, face, veins, etc. With the biometric identification device, the biometric features of a person to be authenticated are registered as enrollment data in advance. When it is necessary for a user to be authenticated, the acquired biometric features are compared with the enrollment data. If they match each other, the user is authenticated. For example, with the vein pattern used in the palm vein identifying method, the markings which appear as the nets of veins are processed as a pattern, and the pattern included in the enrollment data which is registered in advance is compared with the pattern read upon the authentication, thereby authenticating the user. The biometric features of a person fluctuate depending on the state of a living body, such as the age, the condition of a body, etc., and the acquisition state. Therefore, it is necessary to perform comparison with the fluctuations considered. However, if the fluctuation is underestimated, there occurs a no-authentication error (false rejection error). If the fluctuation is overestimated, there occurs a wrong-user acceptance error (false acceptance error). To suppress the fluctuation as much as possible, it is preferable to perform comparison in the same state as the enrollment state. Therefore, a normal biometric identification product acquires biometric information a plurality of times and provides variations in enrollment data, thereby suppressing the fluctuation.
In a palm vein authentication, a noncontact identifying operation is performed without a sensor being touched by a user's hands. In this case, since a vein image is acquired with a user's handheld in the air, the fluctuation of the hand posture (position, tilt, etc.) easily becomes larger in comparison with other modalities. Then, when a user's hand is held on the sensor, there may be a method of introducing the hand to the optimum position while detecting the posture of the held hand so that the optimum state of the posture may be maintained. However, since the method forces the user to hold the hand in a particular posture, the usability is degraded.
On the other hand, when vein images are continuously captured while trailing the moving hand, and compared with appropriate images, the usability may be substantially improved while maintaining high identification accuracy. In this case, it is important to use an appropriate method of selecting enrollment images. If a method of capturing an image with the user's hand in a static position during registration is used, there occurs the problem of degradation in accuracy when a non-optimum image is registered. Furthermore, a change in posture due to having different operating methods between registration and collation may cause a degradation in accuracy.
When a moving hand is continuously captured and compared, it is preferable that a enrollment image be selected from among a set of images obtained by continuously capturing images. The technology of automatically selecting and using an image which is assumed to be the optimum image is loaded into, for example, a digital camera which is loaded with a face identifying system, etc. Even in the biometric identification field, some techniques of selecting the optimum image from among a plurality of acquired images and using the image have been proposed.
For example, it is a well-known technique to capture a plurality of images of biometric features of a face, etc., and record some highly similar images as enrollment images among the captured images.
There are also well-known techniques to have variations by thinning highly similar images by calculating the similarity among images, and to have variations of rotation angles by continuously capturing fingers uncurled in a flat state.
However, in the technique of recording as enrollment data a highly similar image from a plurality of images, the purpose of providing variations to collect highly similar images is not fulfilled.
In addition, in the technique of thinning highly similar images after calculating the similarity among images, and providing variations in rotation angle after continuously capturing fingers uncurled in a flat state, a one-dimensional evaluation criterion is used, and it is difficult to apply the technique when data indicates a multidimensional degree of freedom as in the noncontact palm vein identification. Furthermore, in the noncontact biometric identification device, since different operations are performed between enrollment and comparison of enrollment data, it is not certain that enrollment data appropriate for comparison will be obtained without fail.
In addition, each time a user holds his or her hand for user authentication above the noncontact biometric identification device, the position and direction of the hand easily fluctuates, or the background image is taken undesirably because the hand does not completely cover the capturing area, and thereby various images are acquired undesirably. To successfully authenticate a user by comparing and comparing the acquired images with enrollment data, the enrollment data must have large variations. However, it is difficult to systematically provide such enrollment data.    [Patent Document 1] Japanese Laid-open Patent Publication No. 2007-4321    [Patent Document 2] Japanese Laid-open Patent Publication No. 2007-521577    [Patent Document 3] Japanese Laid-open Patent Publication No. 2009-282706